Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/p47phoenix/claude-plugins/demographicnpx skills add P47Phoenix/Claude-Plugins --skill demographicgit clone --depth 1 https://github.com/P47Phoenix/Claude-PluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/p47phoenix/claude-plugins/demographic)<a href="https://agentmods.dev/skills/p47phoenix/claude-plugins/demographic"><img src="https://agentmods.dev/badge/skills/p47phoenix/claude-plugins/demographic.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00075 | $0.00458 |
| Opus 5 | $0.00037 | $0.00229 |
| Sonnet 5 | $0.00015 | $0.00092 |
| Haiku 4.5 | $0.00007 | $0.00046 |
Grade A, and why
user-feedback-personas-demographic scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Demographic Overlay Personas Sub-Skill
Router-dispatched paradigm sub-skill for demographic-overlay personas. Not directly invokable by the model; the user-feedback parent skill loads this sub-skill when the user requests an overlay (e.g. "Casual Casey as Gen Z") or when the focus-group composition specifies a generational mix.
Personas Covered
| Persona | Profile Section |
|---|---|
| Gen Z Zara | references/persona-library.md § Category 4: Demographic Overlays → Gen Z Zara |
| Millennial Mike | references/persona-library.md § Category 4: Demographic Overlays → Millennial Mike |
| Gen X Grace | references/persona-library.md § Category 4: Demographic Overlays → Gen X Grace |
| Boomer Bob | references/persona-library.md § Category 4: Demographic Overlays → Boomer Bob |
Reference paths above resolve relative to the parent skill delivery-team/skills/user-feedback/.
Overlay Application
Demographic overlays modify communication style, expectations, and reference points without replacing the base persona's category profile. Overlay effect summaries live in ../../references/persona-invocation.md § Overlay Handling. When applying an overlay, append the overlay's modifiers to the base persona profile in the agent prompt; do not replace the base persona's goals, frustrations, or accessibility needs.
Standalone Use
Demographic personas can also be used standalone (without a base category persona) to gather pure generational reaction; weight 0.8x per the parent skill's aggregation rules in such cases.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 34 lines · 75 tokens per session scan A ecc29a101e8a
user-feedback-personas-demographic is a skill published in the GitHub repository P47Phoenix/Claude-Plugins (2 stars, last pushed 3mo ago), licensed MIT. It adds 75 tokens to every session and 458 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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